code: def test_params():
      """[Model Selection] Test raises on bad params."""
      evl = Evaluator(mape_scorer, verbose=2)
  
      np.testing.assert_raises(
          ValueError,
          evl.fit,
          X,
          y,
          estimators=[OLS()],
          param_dicts={"bad.ols": {"offset": randint(1, 10)}},
          preprocessing={"prep": [Scale()]},
      )
  
file_path: mlens/mlens/model_selection/tests/test_model_selection.py
imports: import os
  import numpy
  from mlens.model_selection import Evaluator, benchmark
  from mlens.metrics import mape, make_scorer
  from mlens.utils.exceptions import FitFailedWarning
  from mlens.utils.dummy import OLS, Scale
  from mlens.testing import Data
  from scipy.stats import randint
label_desc: Use image node_id 3 for calling a global function with example usage: test_params() without return types